Soil organic matter (SOM) is key to maintaining soil fertility, mitigating climate change, combatting land degradation, and conserving above- and below-ground biodiversity and associated soil processes and ecosystem services. In order to derive management options for maintaining these essential services provided by soils, policy makers depend on robust, predictive models identifying key drivers of SOM dynamics. Existing SOM models and suggested guidelines for future SOM modelling are defined mostly in terms of plant residue quality and input and microbial decomposition, overlooking the significant regulation provided by soil fauna. The fauna controls almost any aspect of organic matter turnover, foremost by regulating the activity and functional composition of soil microorganisms and their physical–chemical connectivity with soil organic matter. We demonstrate a very strong impact of soil animals on carbon turnover, increasing or decreasing it by several dozen percent, sometimes even turning C sinks into C sources or vice versa. This is demonstrated not only for earthworms and other larger invertebrates but also for smaller fauna such as Collembola. We suggest that inclusion of soil animal activities (plant residue consumption and bioturbation altering the formation, depth, hydraulic properties and physical heterogeneity of soils) can fundamentally affect the predictive outcome of SOM models. Understanding direct and indirect impacts of soil fauna on nutrient availability, carbon sequestration, greenhouse gas emissions and plant growth is key to the understanding of SOM dynamics in the context of global carbon cycling models. We argue that explicit consideration of soil fauna is essential to make realistic modelling predictions on SOM dynamics and to detect expected non-linear responses of SOM dynamics to global change. We present a decision framework, to be further developed through the activities of KEYSOM, a European COST Action, for when mechanistic SOM models include soil fauna. The research activities of KEYSOM, such as field experiments and literature reviews, together with dialogue between empiricists and modellers, will inform how this is to be done.

Change in land use and management can impact massively on soil ecosystems. Ecosystem engineers and other functional biodiversity in soils can be influenced directly by such change and this in turn can affect key soil functions. Here, we employ meta-analysis to provide a quantitative assessment of the effects of changes in land use and land management across a range of successional/extensification transitions (conventional arable → no or reduced tillage → grassland → wooded land) on community metrics for two functionally important soil taxa, earthworms and fungi. An analysis of the relationships between community change and soil structural properties was also included.

The sustainable management of land for agricultural production has at its core a healthy soil, because this reduces the quantity of external inputs, reduces losses of nutrients to the environment, maximises the number of days when the soil can be worked, and has a pore structure that maximises both the retention of water in dry weather and drainage of water in wet weather. Soil health encompasses the physical, chemical, and biological features, but the use of biological indicators is the least well advanced. Sustainability also implies the balanced provision of ecosystem services, which can be more difficult to measure than single indicators. We describe how the key components of the soil food web contribute to a healthy soil and give an overview of the increasing number of scientific studies that have examined the use of biological indicators. A case study is made of the ecosystem service of water infiltration, which is quite an undertaking to measure directly, but which can be inferred from earthworm abundance and biodiversity which is relatively easy to measure. This highlights the difficulty of putting any monitoring scheme into practice and we finish by providing the considerations in starting a new soil health monitoring service in the UK and in maintaining biological monitoring in The Netherlands.

The ecosystem services approach has gained broad interest in regulatory and policy circles for use in ecological risk assessment. Whilst identifying several challenges, scientific experts from European regulatory authorities, the chemical industry and academia considered the approach applicable to all chemical sectors and potentially contributing to greater ecological relevance for setting and assessing environmental protection goals compared to current European regulatory frameworks for chemicals. These challenges were addressed in workshops to develop a common understanding across stakeholders on how the ecosystem services concept might be used in chemical risk assessment and what would need to be done to implement it. This paper describes the consensus outcome of those discussions. Knowledge gaps and research needs were identified and prioritised, exploring the use of novel approaches from ecology, ecotoxicology and ecological modelling. Where applicable, distinction is made between prospective and retrospective ecological risk assessment. For prospective risk assessment the development of environmental scenarios accounting for chemical exposure and ecological conditions was designated as a top priority. For retrospective risk assessment the top priority research need was development of reference conditions for key ecosystem services and guidance for their derivation. Both prospective and retrospective risk assessment would benefit from guidance on the taxa and measurement endpoints relevant to specific ecosystem services and from improved understanding of the relationships between measurement endpoints from standard toxicity tests and the ecosystem services of interest (i.e. assessment endpoints). The development of mechanistic models, which could serve as ecological production functions, was identified as a priority. A conceptual framework for future chemical risk assessment based on an ecosystem services approach is presented.